In just a few months, generative artificial intelligence has established itself as an essential productivity lever. But between the initial enthusiasm and the real gains, there is a gap that only well-prepared organizations manage to bridge.
Start with the right use cases
The temptation is strong to deploy AI everywhere, all at once. Experience shows, however, that the most profitable projects first target specific, repetitive tasks:
- drafting and reviewing documents;
- summarizing minutes and emails;
- searching for information in internal knowledge bases;
- first-level support for employees.
By focusing efforts on a few high-value use cases, you achieve measurable results that lend credibility to the initiative in the eyes of management.
Govern the adoption
A powerful technology without governance quickly becomes a risk.
AI adoption must be accompanied by clear rules: what data may be submitted to the models, what uses are permitted, how to validate the results produced. Compliance with Quebec’s Law 25 (Bill 25) makes this oversight all the more essential.
Measure and adjust
An AI project is never finished. The best teams put simple indicators in place — time saved, user satisfaction, quality of deliverables — and continuously adjust their practices.
It is precisely this gradual, measured approach that sets apart the organizations that profit from AI from those that merely talk about it.